Left Ventricular Segmentation Challenge from Cardiac MRI: A Collation Study

  • Avan Suinesiaputra
  • Brett R. Cowan
  • J. Paul Finn
  • Carissa G. Fonseca
  • Alan H. Kadish
  • Daniel C. Lee
  • Pau Medrano-Gracia
  • Simon K. Warfield
  • Wenchao Tao
  • Alistair A. Young
Part of the Lecture Notes in Computer Science book series (LNCS, volume 7085)

Abstract

This paper presents collated results from the left ventricular (LV) cardiac MRI segmentation challenge as part of STACOM’11. Clinical cases from patients with myocardial infarction (100 test and 100 validation cases) were randomly selected from the Cardiac Atlas Project (CAP) database. Two independent sets of expert (manual) segmentation from different sources that are available from the CAP database were included in this study. Automated segmentations from five groups were contributed in the challenge. The total number of cases with segmentations from all seven raters was 18. For these cases, a ground truth “consensus” segmentation was estimated based on all raters using an Expectation-Maximization (EM) method (the STAPLE algorithm).

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Copyright information

© Springer-Verlag Berlin Heidelberg 2012

Authors and Affiliations

  • Avan Suinesiaputra
    • 1
  • Brett R. Cowan
    • 1
  • J. Paul Finn
    • 2
  • Carissa G. Fonseca
    • 2
  • Alan H. Kadish
    • 3
  • Daniel C. Lee
    • 3
  • Pau Medrano-Gracia
    • 1
  • Simon K. Warfield
    • 4
  • Wenchao Tao
    • 2
  • Alistair A. Young
    • 1
  1. 1.Auckland Bioengineering InstituteUniversity of AucklandNew Zealand
  2. 2.Department of Radiological SciencesUniversity of CaliforniaLos AngelesUSA
  3. 3.Division of CardiologyNorthwestern UniversityUSA
  4. 4.Computational Radiology LaboratoryHarvard Medical SchoolUSA

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